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Grokking Dynamic Programming Interview in Python
The ultimate dynamic programming guide by FAANG engineers. Structured prep with real-world DP questions to get interview-ready in hours!
4.9
53 Lessons
25h
Also available in
Also available in
Join 3 million developers at
Join 3 million developers at
LEARNING OBJECTIVES
- A deep understanding of the essential patterns behind common dynamic programming interview questions—without having to drill endless problem sets
- The ability to identify and apply the underlying pattern in an interview question by assessing the problem statement
- Familiarity with dynamic programming techniques with hands-on practice in a setup-free coding environment
- The ability to efficiently evaluate the tradeoffs between time and space complexity in different solutions
- A flexible conceptual framework for solving any dynamic programming question, by connecting problem characteristics and possible solution techniques
Learning Roadmap
1.
Getting Started
Getting Started
Get familiar with dynamic programming, building concepts, and problem-solving skills for coding interviews.
2.
0/1 Knapsack
0/1 Knapsack
Solve challenges with optimized dynamic programming techniques for various combinatorial problems.
3.
Unbounded Knapsack
Unbounded Knapsack
6 Lessons
6 Lessons
Examine dynamic programming strategies for optimizing unbounded knapsack, ribbon cut, rod cutting, and coin change problems.
4.
Recursive Numbers
Recursive Numbers
12 Lessons
12 Lessons
Enhance your skills in recursive problem-solving with optimized dynamic programming techniques.
5.
Longest Common Substring
Longest Common Substring
16 Lessons
16 Lessons
Solve problems in dynamic programming for various string and sequence optimization tasks.
6.
Palindromic Subsequence
Palindromic Subsequence
6 Lessons
6 Lessons
See how it works to find, optimize, and partition palindromic subsequences and substrings.
Certificate of Completion
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Developed by MAANG Engineers
ABOUT THIS COURSE
Some of the toughest questions in technical interviews require dynamic programming solutions. Dynamic programming (DP) is an advanced optimization technique applied to recursive solutions. However, DP is not a one-size-fits-all technique, and it requires practice to develop the ability to identify the underlying DP patterns. With a strategic approach, coding interview prep for DP problems shouldn’t take more than a few weeks.
This course starts with an introduction to DP and thoroughly discusses five DP patterns. You’ll learn to apply each pattern to several related problems, with a visual representation of the working of the pattern, and learn to appreciate the advantages of DP solutions over naive solutions.
After completing this course, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence.
This course is also available in JavaScript, C++, and Java—with more coming soon!
Trusted by 3 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
V
Vinay Krishnaiah
Software Developer
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